Antibiotic Resistance in a Hospital and in the Lab
A city hospital tracks Escherichia coli infections from 2015 to 2020. In 2015, 12% of E. coli isolates were resistant to antibiotic X; by 2020, 78% were resistant. The hospital uses X heavily, and prescriptions increase each year. In a controlled lab experiment, two large populations of the same E. coli strain are grown for 50 generations. Population A is exposed to a gradually increasing concentration of X, starting below the minimum inhibitory concentration. Population B is grown without X. At the end, 85% of population A is resistant, while 0.1% of population B is resistant. No horizontal gene transfer is detected in either population. A nurse says, 'The bacteria in population A learned to resist the drug because they were exposed to it.' A physician says, 'We should stop using X completely for one year; resistance will disappear.'
1. Explain how the lab experiment supports natural selection as the cause of resistance, rather than the nurse's claim that the bacteria 'learned' to resist the drug.
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The nurse's claim implies that exposure causes a directed, learned change. The lab result contradicts that. Population B was never exposed to antibiotic X, yet about 0.1% of it was resistant at the end. That means resistant variants already existed in the population, produced by random mutation, not by the drug. In population A, exposure to X killed susceptible bacteria; the rare resistant variants survived and reproduced, so their proportion rose to 85% over 50 generations. The antibiotic did not teach the bacteria; it acted as a selective pressure that changed allele frequencies. This is natural selection: heritable variation, differential survival and reproduction, and a change in the population over time. The hospital data show the same pattern on a larger scale.
2. Evaluate the physician's prediction that resistance will disappear after one year without antibiotic X. Include at least two reasons why the outcome is uncertain.
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The prediction is too confident. Stopping X removes the selective advantage of resistance, but it does not instantly remove the resistant alleles. If resistance imposes a fitness cost, resistant bacteria may decline, but one year may not be enough, especially if the cost is small. If the resistance mutation has no cost, or if compensatory mutations restore fitness, resistant strains can persist for a long time. The hospital data show 78% resistance, so even a slow decline would leave many resistant bacteria. Resistance could also remain in other species or in environmental reservoirs, and infection-control practices affect spread. A better prediction is that resistance frequency may fall slowly, and the hospital should monitor it rather than assume it will disappear.
3. What additional evidence from the hospital could strengthen the claim that antibiotic use caused the rise in resistance? Name one alternative explanation that the current data do not rule out.
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The current data show a correlation: resistance rose from 12% to 78% while prescriptions of X increased. To strengthen causation, the hospital could compare resistance rates in wards with different prescribing rates, or track patients before and after a change in prescribing policy. A sharp drop in resistance after reducing X, while other factors stay stable, would be strong evidence. They could also use genetic typing to see whether resistant infections are mostly one spreading clone or many independent mutations. An alternative explanation is clonal spread: a resistant strain may have spread between patients because of poor infection control, not because each infection evolved resistance independently. Another is that the patient population changed, for example more patients with risk factors. The current data alone cannot separate these explanations.